Editorial: A General Framework for Slow Intelligence Systems

Chang, Shi-Kuo

doi:10.1142/s0218194010004578

Cited by 23 publications

(17 citation statements)

References 3 publications

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“…A slow intelligence system SIS typically possesses at least two decision cycles [2]. The first one, the quick decision cycle, provides an instantaneous response to environmental changes.…”

Section: The Abstract Machine Model For Computation Cyclesmentioning

confidence: 99%

Social Network Models for the TDR System

Chang¹

2016

International Conferences on Distributed Multimedia Systems

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Abstract-The TDR system is an experimental multi-level slow intelligence system for personal health care. The TDR system can be used by a single user or a group of users who will interact to understand, maintain and improve each other's state of health. In this paper, we simulate social networks by applying the Abstract Machine model. Two social network models are described: the Circulated Model and the Teacher Student Model. We have incorporated the Teacher Student Model into the Chi super-component of the TDR system and obtained positive experimental results.Keywords-Personal health care system, slow intelligence system, social network, abstract machine model.

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“…A slow intelligence system SIS typically possesses at least two decision cycles [2]. The first one, the quick decision cycle, provides an instantaneous response to environmental changes.…”

Section: The Abstract Machine Model For Computation Cyclesmentioning

confidence: 99%

Social Network Models for the TDR System

Chang¹

2016

International Conferences on Distributed Multimedia Systems

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“…The general characteristics of a slow intelligence system include enumeration, propagation, adaptation, elimination, concentration and multiple decision cycles [1]. In our previous work, an experimental test bed was implemented that allows designers to specify interacting components for slow intelligence systems [2].…”

Section: Slow Intelligence System (Sis) Is a System That (I) Solves Pmentioning

confidence: 99%

TDR System - A Multi-Level Slow Intelligence System for Personal Health Care

Chang

2016

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-This paper describes the design of an experimental multi-level slow intelligence system for health care, called the TDR system, consisting of interacting super-components each with different computation cycles specified by an abstract machine model. The TDR system has three major super-components: Tian (Heaven), Di (Earth) and Ren (Human), which are the essential ingredients of a human-centric psycho-physical system following the Chinese philosophy. Each super-component further consists of interacting components supported by an SIS server. This experimental TDR system provides a platform for exploring and integrating different applications in personal health care, emergency management and social networking.Keywords-slow intelligence system, distributed sensor networks, component-based software engineering.

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“…The slow intelligence approach was first proposed by Shi-Kuo Chang [1]. In this section we will briefly review recently published papers in this area.…”

Section: Related Workmentioning

confidence: 99%

“…An SIS continuously learns, searches for new solutions and propagates and shares its experience with peers [1].…”

Section: Introductionmentioning

confidence: 99%

“…There are many interesting theoretical issues concerning the design of slow intelligence systems [1]. To make the SIS technology useful to the practitioners, in this paper we describe a practical test bed for Slow Intelligence Systems enhanced with super-components, i.e., multiple components that can be activated either sequentially or in parallel and have complex interactions to search for better solutions.…”

Section: Introductionmentioning

confidence: 99%

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A Slow Intelligence System Test Bed Enhanced with Super-Components

Chang¹

2015

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-The slow intelligence system (SIS) technology is a novel technology for the design of a complex information system that is aware of the environment through multiple sensors and capable of improving its performance over time. In this paper we describe a practical slow intelligence system test bed where super-components can be specified to describe interactions among components. These supercomponents are automatically transformed into time controllers for components so they can be managed by the SIS test bed. We illustrate our methodology on personal healthcare system design using this SIS test bed enhanced with super-components.Keywords-slow intelligence system, environment-aware software engineering, super-component, SIS test bed, personal healthcare system.

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Editorial: A General Framework for Slow Intelligence Systems

Cited by 23 publications

References 3 publications

Social Network Models for the TDR System

Social Network Models for the TDR System

TDR System - A Multi-Level Slow Intelligence System for Personal Health Care

A Slow Intelligence System Test Bed Enhanced with Super-Components

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